20
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Urinary metabolomics of young Italian autistic children supports abnormal tryptophan and purine metabolism

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Autism spectrum disorder (ASD) is still diagnosed through behavioral observation, due to a lack of laboratory biomarkers, which could greatly aid clinicians in providing earlier and more reliable diagnoses. Metabolomics on human biofluids provides a sensitive tool to identify metabolite profiles potentially usable as biomarkers for ASD. Initial metabolomic studies, analyzing urines and plasma of ASD and control individuals, suggested that autistic patients may share some metabolic abnormalities, despite several inconsistencies stemming from differences in technology, ethnicity, age range, and definition of “control” status.

          Methods

          ASD-specific urinary metabolomic patterns were explored at an early age in 30 ASD children and 30 matched controls (age range 2–7, M:F = 22:8) using hydrophilic interaction chromatography (HILIC)-UHPLC and mass spectrometry, a highly sensitive, accurate, and unbiased approach. Metabolites were then subjected to multivariate statistical analysis and grouped by metabolic pathway.

          Results

          Urinary metabolites displaying the largest differences between young ASD and control children belonged to the tryptophan and purine metabolic pathways. Also, vitamin B 6, riboflavin, phenylalanine-tyrosine-tryptophan biosynthesis, pantothenate and CoA, and pyrimidine metabolism differed significantly. ASD children preferentially transform tryptophan into xanthurenic acid and quinolinic acid (two catabolites of the kynurenine pathway), at the expense of kynurenic acid and especially of melatonin. Also, the gut microbiome contributes to altered tryptophan metabolism, yielding increased levels of indolyl 3-acetic acid and indolyl lactate.

          Conclusions

          The metabolic pathways most distinctive of young Italian autistic children largely overlap with those found in rodent models of ASD following maternal immune activation or genetic manipulations. These results are consistent with the proposal of a purine-driven cell danger response, accompanied by overproduction of epileptogenic and excitotoxic quinolinic acid, large reductions in melatonin synthesis, and gut dysbiosis. These metabolic abnormalities could underlie several comorbidities frequently associated to ASD, such as seizures, sleep disorders, and gastrointestinal symptoms, and could contribute to autism severity. Their diagnostic sensitivity, disease-specificity, and interethnic variability will merit further investigation.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13229-016-0109-5) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references56

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          MetaboAnalyst 2.0—a comprehensive server for metabolomic data analysis

          First released in 2009, MetaboAnalyst (www.metaboanalyst.ca) was a relatively simple web server designed to facilitate metabolomic data processing and statistical analysis. With continuing advances in metabolomics along with constant user feedback, it became clear that a substantial upgrade to the original server was necessary. MetaboAnalyst 2.0, which is the successor to MetaboAnalyst, represents just such an upgrade. MetaboAnalyst 2.0 now contains dozens of new features and functions including new procedures for data filtering, data editing and data normalization. It also supports multi-group data analysis, two-factor analysis as well as time-series data analysis. These new functions have also been supplemented with: (i) a quality-control module that allows users to evaluate their data quality before conducting any analysis, (ii) a functional enrichment analysis module that allows users to identify biologically meaningful patterns using metabolite set enrichment analysis and (iii) a metabolic pathway analysis module that allows users to perform pathway analysis and visualization for 15 different model organisms. In developing MetaboAnalyst 2.0 we have also substantially improved its graphical presentation tools. All images are now generated using anti-aliasing and are available over a range of resolutions, sizes and formats (PNG, TIFF, PDF, PostScript, or SVG). To improve its performance, MetaboAnalyst 2.0 is now hosted on a much more powerful server with substantially modified code to take advantage the server’s multi-core CPUs for computationally intensive tasks. MetaboAnalyst 2.0 also maintains a collection of 50 or more FAQs and more than a dozen tutorials compiled from user queries and requests. A downloadable version of MetaboAnalyst 2.0, along detailed instructions for local installation is now available as well.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Metabolomic analysis and visualization engine for LC-MS data.

            Metabolomic analysis by liquid chromatography-high-resolution mass spectrometry results in data sets with thousands of features arising from metabolites, fragments, isotopes, and adducts. Here we describe a software package, Metabolomic Analysis and Visualization ENgine (MAVEN), designed for efficient interactive analysis of LC-MS data, including in the presence of isotope labeling. The software contains tools for all aspects of the data analysis process, from feature extraction to pathway-based graphical data display. To facilitate data validation, a machine learning algorithm automatically assesses peak quality. Users interact with raw data primarily in the form of extracted ion chromatograms, which are displayed with overlaid circles indicating peak quality, and bar graphs of peak intensities for both unlabeled and isotope-labeled metabolite forms. Click-based navigation leads to additional information, such as raw data for specific isotopic forms or for metabolites changing significantly between conditions. Fast data processing algorithms result in nearly delay-free browsing. Drop-down menus provide tools for the overlay of data onto pathway maps. These tools enable animating series of pathway graphs, e.g., to show propagation of labeled forms through a metabolic network. MAVEN is released under an open source license at http://maven.princeton.edu.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Microglial activation and increased microglial density observed in the dorsolateral prefrontal cortex in autism.

              In the neurodevelopmental disorder autism, several neuroimmune abnormalities have been reported. However, it is unknown whether microglial somal volume or density are altered in the cortex and whether any alteration is associated with age or other potential covariates. Microglia in sections from the dorsolateral prefrontal cortex of nonmacrencephalic male cases with autism (n = 13) and control cases (n = 9) were visualized via ionized calcium binding adapter molecule 1 immunohistochemistry. In addition to a neuropathological assessment, microglial cell density was stereologically estimated via optical fractionator and average somal volume was quantified via isotropic nucleator. Microglia appeared markedly activated in 5 of 13 cases with autism, including 2 of 3 under age 6, and marginally activated in an additional 4 of 13 cases. Morphological alterations included somal enlargement, process retraction and thickening, and extension of filopodia from processes. Average microglial somal volume was significantly increased in white matter (p = .013), with a trend in gray matter (p = .098). Microglial cell density was increased in gray matter (p = .002). Seizure history did not influence any activation measure. The activation profile described represents a neuropathological alteration in a sizeable fraction of cases with autism. Given its early presence, microglial activation may play a central role in the pathogenesis of autism in a substantial proportion of patients. Alternatively, activation may represent a response of the innate neuroimmune system to synaptic, neuronal, or neuronal network disturbances, or reflect genetic and/or environmental abnormalities impacting multiple cellular populations. Copyright 2010 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.
                Bookmark

                Author and article information

                Contributors
                gevi@unitus.it
                zolla@unitus.it
                stefano.gabrile@hotmail.com
                apersico@unime.it
                Journal
                Mol Autism
                Mol Autism
                Molecular Autism
                BioMed Central (London )
                2040-2392
                24 November 2016
                24 November 2016
                2016
                : 7
                : 47
                Affiliations
                [1 ]Department of Ecological and Biological Sciences, University of Tuscia, Viterbo, Italy
                [2 ]Unit of Child and Adolescent Neuropsychiatry, Laboratory of Molecular Psychiatry and Neurogenetics, University Campus Bio-Medico, Rome, Italy
                [3 ]Unit of Child and Adolescent Neuropsychiatry, Interdepartmental Program “Autism 0-90”, “Gaetano Martino” University Hospital, University of Messina, Messina, Italy
                [4 ]Mafalda Luce Center for Pervasive Developmental Disorders, Milan, Italy
                Article
                109
                10.1186/s13229-016-0109-5
                5121959
                27904735
                3103c719-ee3f-4f75-8862-67980ea5c9c8
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 25 December 2015
                : 11 November 2016
                Funding
                Funded by: Italian Ministry for University, Scientific Research and Technology
                Award ID: PRIN n.2006058195
                Award Recipient :
                Funded by: Italian Ministry of Health
                Award ID: CCM2012
                Award Recipient :
                Funded by: Fondazione Gaetano e Mafalda Luce (Milan, Italy)
                Funded by: FundRef http://dx.doi.org/10.13039/100007332, Autism Research Institute ;
                Funded by: Innovative Medicines Initiative Joint Undertaking
                Award ID: EU-AIMS 115300
                Award Recipient :
                Funded by: Interuniversity Consortium for Biotechnologies
                Award ID: mobility studentship funds and post-doctoral research grant
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2016

                Neurosciences
                autism,autism spectrum disorder,kynurenine,melatonin,metabolomics,purinergic signaling,quinolinic acid,serotonin,tryptophan

                Comments

                Comment on this article